limebit/medmodels

MedModels is a high-speed RWE framework to apply the latest methods from scientific research to medical data.

31
/ 100
Emerging

This framework helps medical researchers, epidemiologists, and health economists efficiently analyze complex patient data from electronic health records (EHR) and claims. It transforms raw medical data into standardized, high-performance graph structures, allowing users to apply advanced statistical methods for treatment effect analysis. The output provides insights into patient outcomes and treatment effectiveness, helping to inform clinical and public health decisions.

Use this if you need to analyze large-scale real-world medical data, streamline your research workflows, and accurately estimate treatment effects from observational patient records.

Not ideal if you are working with small, simple datasets or do not require advanced statistical modeling and graph-based data structures for your medical research.

medical-research epidemiology health-economics real-world-evidence treatment-effect-analysis
No Package No Dependents
Maintenance 10 / 25
Adoption 5 / 25
Maturity 16 / 25
Community 0 / 25

How are scores calculated?

Stars

11

Forks

Language

Python

License

BSD-3-Clause

Last pushed

Jan 23, 2026

Commits (30d)

0

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